Event tagging for mobile networks

ABSTRACT

Improved network event tagging for mobile communications is described herein. By way of example, a mobile network can be configured to take periodic geographic positions of a mobile terminal operating within the mobile network. Network events occurring between the periodic geographic positions, otherwise partially unknown in position, can be estimated by referencing topographical information and estimating a route of travel of the mobile device. Estimated speed of the mobile device can be utilized to place the mobile device on a road network, cycling route, pedestrian walkway, or the like, and refine the estimated position of the mobile device at the time of the network event. Such estimates can be refined from traffic information or other real-time travel data. An estimated position of the mobile device can be output as an approximation of the network event to facilitate event modeling for the mobile network.

RELATED APPLICATION

The subject application is a continuation of, and claims priority to,U.S. patent application Ser. No. 13/494,959 (now U.S. Pat. No.9,094,929), filed Jun. 12, 2012, and entitled “EVENT TAGGING FOR MOBILENETWORKS.” The entirety of the foregoing application is herebyincorporated by reference herein.

TECHNICAL FIELD

The subject application relates in general to managing activity within awireless network and more particularly to providing event tagging formobile networks.

BACKGROUND

Wireless communication networks provide a diverse set of voice and datacommunication services for subscribers via mobile handsets and relatedmobile communication devices. A terrestrial radio access network isemployed to transmit and receive information wirelessly to the mobilehandsets, enabling subscribers to move with their mobile handsets whilemaintaining communication with the wireless communication network. If anevent occurs that disrupts the transmission or reception of informationbetween the mobile handset and the radio access network, quality ofcommunication can be negatively affected and, in severe cases, thecommunication can be interrupted entirely. Common causes of such eventscan include natural or electromechanical interference, signalattenuation from intervening objects or the like, signal scatteringphenomenon, and so on. These and similar events are common causes ofdisruptions in wireless communication. They also present a dynamicchallenge for network operators attempting to achieve high quality ofservice for subscribers.

In order to qualify the problem of network communication problems foranalysis and correction, network operators often record calldisturbances after they occur. For instance, if a particular call ordata session is terminated without proper communication protocol, thetermination can be tagged as a call drop. Certain information about thecall drop can be recorded to study the event. Suitable information caninclude time of the call drop, and the base station(s) serving theparticular call or data session. Since the location of network basestations are known, recording the base station(s) serving the particularcall or data session gives an estimate of location of the call drop. Thetime of the call drop and the base station(s) and its location(s) can berecorded as an event by a mobile network.

Call drop events can be aggregated and analyzed over time as areflection of network regions with increased likelihood of communicationproblems. Network operators can address these problems by bolsteringradio access network infrastructure in a problem region, addingspecialized equipment such as micro or mini base stations, setting uprepeater base stations to avoid or mitigate interference, and so on.General knowledge of call drop events can provide a first degree ofapproximation of underlying problems.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example system that providesnetwork event modeling in mobile communications in aspects of thesubject disclosure.

FIG. 2 depicts a block diagram of a sample estimation engine forestimating position of a mobile device at a time of a network event, inother aspects.

FIG. 3 illustrates a diagram of an example area map for estimating aposition of a mobile device from a known set of positions of the mobiledevice.

FIG. 4 depicts a diagram of a sample topographical map utilized inconjunction with estimating a position of a mobile device along a routeof travel.

FIG. 5 illustrates a block diagram of an example network environment foraggregating network and topographical data for estimating mobile deviceposition.

FIG. 6 depicts a flowchart of an example method for providing networkevent modeling according to one or more aspects.

FIGS. 7 and 8 illustrate a flowchart of an example method for improvingnetwork event modeling with topographical data in mobile positionlocations.

FIG. 9 depicts a block diagram of an example computer-readable mediumfor providing network event modeling according to particular aspects.

FIG. 10 illustrates a block diagram of a sample mobile handset that canbe configured for operation in conjunction with one or more disclosedaspects.

FIG. 11 illustrates a block diagram of an example radio access networkdevice that can be operable for facilitating various disclosed aspects.

FIG. 12 depicts a block diagram of an example wireless communicationnetwork that can be operable for facilitating additional aspects.

DETAILED DESCRIPTION

The disclosed subject matter is now described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the disclosed subject matter. It may beevident, however, that the disclosed subject matter can be practicedwithout these specific details. In other instances, structures anddevices are shown in block diagram form to facilitate describing thedisclosed subject matter.

Where used in this application, the terms “component,” “system,”module”, “interface,” and the like are intended to refer to acomputer-related entity or an entity related to an operational apparatuswith one or more specific functionalities, wherein the entity can beeither hardware, a combination of hardware and software, software, orsoftware in execution. As an example, a component may be, but is notlimited to being, a process running on a processor, a processor, acircuit, a logic gate, an object, an executable, a thread of execution,computer-executable instructions, a program, or a computer. By way ofillustration, both an application running on a server/client and theserver/client can be a component. One or more components can residewithin a process or thread of execution and a component can be localizedon one computer or distributed between two or more computers. Also,components can execute from various computer readable media havingvarious data structures stored thereon. The components may communicatevia local or remote processes such as in accordance with a signal havingone or more symbols, data packets, etc. (e.g., data from one componentinteracting with another component in a local system, distributedsystem, and/or across a network such as the Internet with other systemsvia the signal). As another example, a component can be an apparatuswith specific functionality provided by mechanical parts operated byelectric or electronic circuitry, which can be operated by a software orfirmware application executed by a processor, wherein the processor canbe internal or external to the apparatus and executes at least a part ofthe software or firmware application. As yet another example, acomponent can be an apparatus that provides specific functionalitythrough electronic components without mechanical parts, the electroniccomponents can include a processor, a state machine, an integratedcircuit, etc., therein to execute software or firmware that confers atleast in part the functionality of the electronic components.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A, X employs B, or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should be construed to mean“one or more” unless specified otherwise or clear from context to bedirected to a singular form.

Moreover, terms like “user equipment (UE),” “mobile station,” “mobile,”subscriber station,” “subscriber equipment,” “access terminal,”“terminal,” “handset,” and similar terminology, refer to a wirelessdevice utilized by a subscriber or user of a wireless communicationservice to receive or convey data, control, voice, video, sound, gaming,or other suitable data-stream or signaling-stream. The foregoing termsare utilized interchangeably in the subject specification and relateddrawings. Likewise, the terms “access point (AP),” “base station,” “NodeB,” “evolved Node B (eNode B),” “home Node B (HNB),” “home access point(HAP),” and the like, refer to a wireless network component or appliancethat serves and receives data, control, voice, video, sound, gaming, orother suitable data-stream or signaling-stream from a set of subscriberstations, except where context or definition warrants distinctions amongthe term(s). Data and signaling streams can be packetized or frame-basedflows.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer,”“prosumer,” “agent,” and the like are employed interchangeablythroughout the subject specification, unless context warrants particulardistinction(s) among the terms. It should be appreciated that such termscan refer to human entities or automated components supported throughartificial intelligence (e.g., a capacity to make inference based oncomplex mathematical formalisms) which can provide simulated vision,sound recognition and so forth.

Increase in consumer use of wireless communication and near ubiquitouspenetration of mobile electronic communication devices within theconsumer public has put great demand on mobile communication serviceproviders. This demand can vary, depending on content consumed bysectors of the public. In addition, demand for different services canvary widely as a function of service, and as a function of geography.For instance, streaming media and web browsing patronized extensively byyounger subscribers can be in much higher demand near high school orcollege campuses, as compared with average demand patterns throughoutthe network. In addition, messaging services and particular enterprisemessaging can be in higher demand near office buildings. Voice traffic,on the other hand can be in high demand where population densities arehigher in general. Because communication quality is often servicedependent, temporal or systemic network communication problems can havesignificant impact on all services, but affect high quality services inparticular.

To identify network problems, network operators can track and locatelocation-based network events. A location-based network event can bedefined as a wireless communication action in which a wireless networkhas at least some information related to a location of a mobile deviceassociated with such an action. Location-based network events cancomprise a call start, a call termination, a report of substandardservice, a call drop (for voice or data calls), or a similar event, or asuitable combination thereof. A problem event can compriselocation-based events related to poor or substandard service, such asthe report of substandard service and the call drop. By tracking problemevents in time and location, anomalies can be identified within anetwork that observe more frequent call drop or substandard serviceevents. These regions can be addressed with greater priority to fix theproblem.

Overall, network operators track, record and analyze location-basednetwork events as a mechanism for proper maintenance and optimization ofa wireless network. Traditional methods of network diagnostics,including extensive drive testing, can be both time consuming andexpensive. Moreover, results of extensive drive tests lose relevanceafter they are post processed and analyzed. To model dynamic conditionsof wireless networks, however, network operators require informationabout network events in near real time. Otherwise, timely response tothose events is very difficult. In this regard, as more informationabout a problem is discovered, the problem can be modeled with greaterdegrees of accuracy, leading to more effective solutions. Thus, networkevent modeling is one aspect of network maintenance that meritssignificant improvement, not only to further define modeling ofproblems, but to facilitate more cost effective solutions closelytailored to solve a particular problem with minimum required resources.

With new technologies, greater accuracy of network events and mobileposition locations are possible. Examples of such technology includemobile location determinations from radio access network signaling,existing technologies that make use of e911 platforms for locatingmobile devices, global positioning systems (GPS), assisted GPS or A-GPS,and so on. These technologies can make mobile location determinationsvery precise. However, network events and mobile location determinationscan be uncoordinated in time, as occurrences of network events can havevarious causes and are often unpredictable.

Because network events themselves are often not known with muchaccuracy, a simple approach to estimate location of a network event ispeg the network event to the cell serving a mobile device related to thenetwork event (e.g., a mobile handset experiencing a call drop). Thisrough positioning can yield little practical information for location asource of interference, however. This can be especially true, forinstance, in the case of a small transmitter that interferes in anon-continuous, and especially a non-periodic manner. Without moreaccurate estimates of network event location, quickly and accuratelyidentifying a source of a problem event can be exhaustive, expensive,and sometimes impossible.

To address problems associated with network event modeling, the subjectdisclosure provides for marrying location-based network event data withmobile device location data. A best estimate of mobile device positionat a time of a network event is generated and associated with a positionof the network event, instead of simply associating the network eventwith a cell location or cell site. This enables network operators tomore accurately model network related issues. Accurate modeling ofissues further enables network engineers to optimize network coveragemodels and implement network configuration and coverage objectives,improving network performance and perception by the subscriber base.

In some aspects of the subject disclosure, provided is an improvedmechanism for network event modeling. The disclosed network eventmodeling can extrapolate known mobile device locations to estimate aposition of a mobile device for a mobile device position that is atleast in part unknown. Extrapolation and interpolation algorithms can beemployed to extend mobile positioning beyond a known position data set,in various aspects, providing greater resolution in time and space ofmobile device position, thereby providing much greater accuracy andsignificance to network event modeling overall.

In further aspects of the subject disclosure, periodic mobile deviceposition data can be utilized in conjunction with network event data toestimate mobile device position in-between periodic position signaling.In at least one aspect, position of a mobile device during a networkevent can be estimated by extrapolating between two or more knownpositions of the mobile device based on relative analysis of respectivetimes of those position determinations and of the network event.Further, an estimated position of the mobile device can be enhanced byaccessing additional information in a known locality of the mobiledevice.

In at least one aspect, topographical information can be leveraged torefine a position estimate of a mobile device. For instance, if themobile device is determined to be traveling at a time of the networkevent, a set of topographical maps representing known routes of travelfor a set of modes of travel can be referenced to locate the mobiledevice on a particular route of travel. By locating the device on aknown travel route, accuracy of a position estimate can be significantlyenhanced, thereby further enhancing the location of the network event.

In other aspects, an estimate of speed of travel of the mobile devicecan be derived from known location and timing information. The speed oftravel can be matched to one or more modes of travel to identify aparticular mode of travel employed by a subscriber. By identifying theparticular mode of travel, a more accurate estimate of travel route canbe obtained as well. For instance, if the speed estimate matches speedsexpected from motor vehicle travel, the position estimate can beconfined to roads or highways to refine the estimated position. Asanother example, if the speed estimate matches speeds expected fromcycling, the position estimate can be confined to cycling routes. As yetanother example, if the speed estimate matches speeds expected frompedestrian traffic, the position estimate can be confined to pedestrianroutes, and so on. Upon identifying a particular mode of travel, atopographical map of the mode of travel within a vicinity of the knownlocation points of the mobile device can be utilized to identify a routeof travel employed by the subscriber, and a position along the route oftravel at which the network event occurred.

In one or more additional aspects, traffic data can be utilized tofurther refine position estimates of a mobile device. For instance,dynamic traffic information can give a more accurate estimate of motorvehicle speeds than static traffic information, such as a speed limit.Thus, where dynamic traffic information exists indicating that trafficon a particular road or highway is greater than or less than knownstatic traffic information, a speed estimate of the mobile device can befurther refined based on the dynamic traffic information. This can beuseful in refining a position of the mobile device on a particular roador highway.

In further aspects of the subject disclosure, a position estimate of amobile device at a time of a network event can be attributed to thenetwork event. This position estimate can therefore be output fornetwork event modeling. In at least one aspect, network event modelsbased on such position estimates can be updated by later acquiredinformation, such as subscriber-initiated position signaling following adropped call, or automated device position signaling in response to thedropped call, or the like. Location information originated at a mobiledevice can often be available much later than network-identified calldrop event data, as well as periodic mobile position informationgenerated by network components. However, this later acquiredinformation can be utilized to update or refine network event modelingonce acquired at the network, in at least some disclosed aspects.

The following description and the annexed drawings set forth in detailcertain illustrative aspects of the disclosed subject matter. Theseaspects are indicative, however, of but a few of the various ways inwhich the principles disclosed herein can be employed and the disclosedsubject matter is intended to include all such aspects and theirequivalents. Other aspects and features of the disclosed subject matterwill become apparent from the following detailed description whenconsidered in conjunction with the drawings.

In some aspects of the subject disclosure, interpolation orextrapolation techniques can be employed to best estimate a mobiledevice location from a set of known device locations, at a time of anetwork event. This estimation can be repeated for each network event,yielding a set of position information for each network event. In aparticular aspect, topographical travel routes can be employed to bestweight segments of a user's travel route and arrive at a best estimateof mobile device location from extrapolation or interpolation of knownmobile locations (e.g., derived from e911 processes, mobile-originatedlocation signaling, GPS-related position determination, periodic radioaccess network position determinations, . . . ) and associated times ofsuch known mobile locations. In other aspects, multiple positionestimates can be employed, in an aggregate, to reduce mobile devicelocation error attributed to respective network events. In furtheraspects, speed estimates can be utilized to identify a particular modeof travel employed by a subscriber, such as motor vehicle, bicycle,pedestrian, etc. Utilizing the mode of travel, a mobile device positionestimate can be located within the boundaries of a road, bicycle lane,sidewalk, building, and so on. Speed estimates can be further enhancedby use of concurrent traffic information, where available, to improvespeed estimates over static traffic speed information such as a speedlimit. Speed estimates can be utilized to best estimate a position alongan identified route of travel at a point in time matching the networkevent.

In a particular aspect of the subject disclosure, network events can becaptured from IuB interfaces via probe networks installed by a networkoperator. The IuB probes can be configured to monitor user traffic andprovide specific network events of concern (e.g., problem events) tonetwork operators. IuB based locating systems, and other location basedsystem (LBS) platforms can be leveraged to generate position informationfor respective network events.

Referring to the drawings, FIG. 1 illustrates a block diagram of anexample system 100 for providing network event tagging for wirelesscommunications, according to various aspects of the subject disclosure.System 100 can comprise an event location system 102 communicativelyconnected with one or more mobile network components 104 over one ormore network interfaces. Mobile network components 104 can comprise aset of entities configured for acquiring information pertaining tomobile location positioning. Mobile network components 104 can includeentities that acquire periodic mobile positions, and entities thatacquire mobile positions non-periodically, randomly, or the like. Inaddition, mobile network components 104 can comprise position datagenerated by network entities, or mobile originated position data.Examples of mobile network components 104 that generate networkoriginated position data can include an e911 location server, an LBSplatform that derives mobile device position from a networkmulti-lateration process, an IuB based locating system, a timedfingerprint location process (e.g., as provided in U.S. patentapplication Ser. No. 12/724,424 entitled Timed Fingerprint Location inWireless Networks and filed Feb. 25, 2010, incorporated by referenceherein), or another suitable network-facilitated mobile positioningmechanism. Examples of mobile network components 104 that employ mobileoriginated position data can include a database that receives and storesmobile-originated GPS data, or the like.

Location information for one or more mobile devices along with timing ofrespective location determinations can be forwarded by mobile networkcomponent(s) 104 to an event location system 102 in a mobile data file105 over the network interface(s). Event location system 102 cancomprise a communication interface 106 for sending and receiving dataover the network interface(s). Thus, mobile data file 105 can bereceived at communication interface 106 and made available to othercomponents of event location system 102. Mobile data file 105 can besaved, for instance, in memory 108 and accessed and utilized by aprocessor 110. Memory 108 can be further configured to storecomputer-executable instructions of event location system 102 andrespective components thereof. Processor 110 can be configured tofacilitate execution of the computer-executable instructions toimplement functionality of event location system 102, as described inmore detail below.

Event location system 102 can further comprise an estimation engine 112configured to estimate position location information for mobile devicesoperating within a mobile network, for periods in which mobile devicepositioning is at least in part unknown. Particularly, positionlocations of a mobile device can be estimated from a set of knownposition data for the mobile device. For instance, periodic mobiledevice position location information can comprise location informationtaken at periodic times, random times, non-periodic times such assubscriber origination position reporting, e911 calls, or the like, or asuitable combination thereof. This information comprises a set of knownposition locations for the mobile device. Utilizing the set of knownposition locations and respective associated points in time, estimationengine 112 can extrapolate position locations of the mobile device atother times. As an example, a data input indicative of a geographiclocation of a mobile device at a first time and a second data inputindicative of a second geographic location of the mobile device at asecond time, can be utilized to extrapolate a third geographic locationof the mobile device at a third time subsequent the first time and thesecond time. As another example, the data input and the second datainput can be utilized to interpolate a fourth geographic location of themobile device at a fourth time between the first time and the secondtime.

Estimation engine 112 can acquire position location information andrespective associated times of one or more mobile devices fromcommunication interface 106, or from memory 108. A data compilationcomponent 114 can parse and categorize the position locations as afunction of mobile device, and as a function of respective times ofrespective position locations. A calculation component 116 can beconfigured to interpolate or extrapolate position information for one ormore of the mobile devices at other times, for which position locationinformation of the respective mobile devices is not available.

In at least one aspect of the subject disclosure, calculation component116 can reference a topography database 118 to acquire topographicalinformation for improving estimates of mobile device locations. Forinstance, if a network event associated with a particular mobile deviceoccurs at a particular point in time, calculation component 116 can lookup position location information from the known set of position locationinformation of the particular mobile device compiled by data compilationcomponent 114, at times near the particular point in time. Additionally,topographical information can be acquired for a particular geographicregion in a vicinity of position locations of the mobile device at thetimes near the particular point in time (e.g., see FIG. 3 and FIG. 4,infra). This topographical information can be utilized to identifysuitable routes of travel within the particular geographic region tolocate the mobile device along a route of travel matching the positionlocations at the times near the particular point in time. By locatingthe mobile device along a particular route of travel, accuracy of alocation estimate for the mobile device can be improved overextrapolation or interpolation estimates alone.

According to further aspects of the subject disclosure, calculationcomponent 116 can estimate a speed of the mobile device at a timeproximate a network event (e.g., a dropped call). The estimated speedcan be matched to predetermined speeds associated with one or more modesof travel. Example modes of travel can include vehicular travel, bicycletravel, pedestrian travel, or the like, which have fairly reliablerespective ranges of speed associated therewith. Thus, for instance, amotorized mode of travel can be associated with speeds 25 miles per hourand greater, a cycling mode of travel can be associated with speedsbetween about 7 and about 20 miles per hour, whereas a pedestrian modeof travel can be associated with speeds between about 0 and 5 miles perhour. Other speed ranges can be associated with these modes of travel orother suitable modes of travel; the foregoing example is not exclusive.In some aspects the ranges of speeds can at least in part overlap,whereas in other aspects the ranges of speeds can be exclusive as in theexample above.

According to these further aspects, upon estimating the speed of themobile device near the time of the network event, calculation component116 can compare the estimated speed to a set of predetermined ranges ofspeed associated with a set of modes of travel. A subset of the set ofmodes of travel can be selected from the set of modes of travel, inresponse to the estimated speed matching one (or more) of the ranges ofspeed. In the example given above, for instance, if the estimated speedof the mobile device is 40 miles per hour, then the motorized mode oftravel can be selected, whereas if the estimated speed is 5 miles perhour, then the pedestrian or cycling modes of travel can be selected.

Upon selecting a mode of travel, calculation component 116 can referencetopography database 118 and obtain topography information for ageographic region in which the mobile device is known to be located(from mobile location data obtained from mobile network component(s)104) near the time of the network event. The topography information caninclude suitable routes of travel (e.g., roads, bicycle lanes or paths,pedestrian routes such as sidewalks, buildings, malls, etc.) for theselected subset of modes of travel. An inference can then be made thatthe mobile device is located along a suitable route of travel that bestmatches known locations of the mobile device. Because routes of travelcan be relatively small in at least one geographic dimension (e.g., abicycle lane or road having a width only one or a few meters), estimatesof the location of the mobile device can be improved during times whenmobile location is not accurately known. For instance, if a mobiledevice is inferred to be on a city street at a time of the networkevent, potential locations of the mobile device can be narrowed to thegeographic limits of the road, at a location between known locations onthe road (e.g., see FIG. 4, infra). A position estimate of the mobiledevice at a time of a network event can then be attributed to a positionof a cause of a network event. This can significantly improve resolutionof network event location estimates over estimates that place a networkevent in an entire cell of a wireless network. This improved resolutionof network event locations can significantly improve network event timeand location modeling, further enhancing effectiveness of networkmaintenance and optimization efforts, thereby improving overall efficacyof wireless communication services.

FIG. 2 depicts a block diagram of an estimation engine 200 according toparticular aspects of the subject disclosure. Estimation engine 200 canbe substantially similar to estimation engine 112 of FIG. 1, supra, insome aspects of the subject disclosure. In alternative or additionalaspects, estimation engine 200 can have a subset of features ofestimation engine 112 or additional features described below, in otheraspects.

Estimation engine 200 can comprise a data compilation component 202 thatacquires time and location event data pertinent to a wireless network.The time and location event data can include time and location positionsof mobile devices operating within the wireless network, as well as timeor location information of network events pertinent to the mobiledevices, or a suitable combination thereof. Data compilation component202 can parse the time and location information, and compile amulti-dimensional matrix that categorizes time and location informationas a function of mobile device, network events, or other suitablecategories.

A calculation component 204 can acquire the compiled matrix of time andlocation information and estimate positions of one or more mobiledevices at times in which mobile device position is not accuratelyknown. Particularly, calculation component 204 can estimate a positionof a mobile device at a time of a network event pertaining to the mobiledevice. As a specific example, calculation component 204 can estimate aposition of a mobile device at a time in which the mobile deviceexperiences a call drop, utilizing a time of the call drop, and locationinformation of the mobile device at times near the call drop.

Calculation component 204 can comprise a set of rate of travelalgorithms 206 for estimating a speed of the mobile device. Rate oftravel algorithms 206 can employ time and location data near a time of anetwork event, and output a speed estimate of the mobile device for aperiod of time that includes or is proximate to the time of the networkevent. As one example, if the time and location data indicate the mobiledevice covers a quarter of a mile (from two or more location points) in30 seconds (from two or more times associated with respective locationpoints), rate of travel algorithms 206 can output an average speed of 30miles per hour as the speed estimate, or another suitable speedcalculation (e.g., a median speed, . . . ) depending on a particularcalculation(s) employed by the rate of travel algorithms 206.

The estimated speed generated by calculation component 204 can beprovided to a topography selection component 208. Topography selectioncomponent 208 can compare the speed estimate to a set of correlationsthat link ranges of speeds with a set of modes of travel. By matchingthe speed estimate to the ranges of speeds, a subset of the modes oftravel can be selected. A map selection(s) can be provided to atopography database 210 that stores mode of travel maps 212. Examplemode of travel maps can include road network map data 214, cycling routedata 216, pedestrian route data 218, and map data for other suitablemodes of travel. Topography database 210 can reply with selected mapdata, which can be forwarded by topography selection component 208 tocalculation component 204.

Upon receiving a selected map(s) of travel routes, calculation component204 can focus on a region of the selected map(s) proximate the locationinformation of the mobile device near the time of the network event.Further, a particular route(s) of travel can be identified that bestmatches known locations of the mobile device. Where the network eventoccurs before or after a set of known locations of the mobile device, aset of extrapolation algorithms 220 can be employed to extrapolate aposition of the mobile device near or at a time of the network event.Where the network event occurs between a set of known locations of themobile device, a set of interpolation algorithms 222 can be employed tointerpolate a position of the mobile device near or at the time of thenetwork event. In some aspects, a combination of extrapolation orinterpolation can be employed, depending on time-based relatedness ofknown locations of the mobile device and the network event.

To estimate a position of the mobile device at a time of the networkevent, calculation component 204 can best match known locations of themobile device with one or more possible routes of travel (e.g., roads,bicycle paths, pedestrian routes, . . . ). From knowledge of the time ofthe network event and when this time occurs relative to times of knownlocations of the mobile device, a position estimate for the mobiledevice can be inferred along a possible route(s) of travel. Wheremultiple possible routes of travel are identified for the mobile device,a best fit algorithm can be employed to best match position locationsand estimated speed of the mobile device to a best fit route of travelto arrive at a best fit position location for the mobile device. Thisbest fit position location can be utilized as a position locationestimate.

In at least one aspect of the subject disclosure, calculation component204 can acquire traffic speed information for a particular route oftravel to refine a position location estimate of the mobile device. Forinstance, if the best fit route of travel is a highway, calculationcomponent 204 can query a network (e.g., the Internet, a server of atraffic information service, municipal, country or state trafficinformation, . . . ) for concurrent traffic information pertaining tothe best fit route of travel, or stored traffic information for priortimes coinciding with the network event. Utilizing traffic speedinformation, a speed of the mobile device along the best fit route oftravel can be refined. The refined speed can then be employed to refinea position of the mobile device along the best fit route of travel at ornear the network event. This refined position can be output as theposition location estimate of the mobile device.

Once the position location estimate of the mobile device at or near thenetwork event is acquired, the position location estimate can beprovided to an output component 224. Output component 224 can transmitthe position location estimate to other components of a wirelessnetwork. This position location estimate can be updated to network eventmodeling functions, to improve the accuracy and resolution of suchfunctions (e.g., see FIG. 5, infra).

FIG. 3 depicts a diagram of an example geographic region 300 in which aposition location of a mobile device operating within a wireless networkcan be inferred for geographic region 300. In some aspects, the positionlocation can be extrapolated from location information of the mobiledevice generated prior to or subsequent to a time of interest (e.g., atime at which a network event occurs). In other aspects, the positionlocation can be interpolated from location information of the mobiledevice that is generated prior to and subsequent to the time ofinterest.

Geographic region 300 is marked with several points of interest. Thepoints of interest are correlated at least with a time stamp, and someor all of the points of interest can be correlated with locationinformation of a mobile device associated with the points of interest.At 302, a periodic location of the mobile device is generated at aposition indicated by a location event symbol comprising an X embeddedin a square. The periodic location can be generated by a component ofthe mobile device (e.g., periodic GPS transmission, . . . ) or can begenerated by a network component (e.g., base station multi-laterationprocess, timed fingerprint location process, . . . ). At 304, a call isinitiated or terminated by the mobile device. An actual location of themobile device is indicated on geographic region 300 by a call symbol ofa check mark embedded in a square, at reference number 304. The callinitiation/termination can be associated at least with a time stamp forthe call, and in some networks location information of the mobile devicecan also be generated for the call initiation/termination identifyingthe actual location of the mobile device at the time of the call. At306, a problem event occurs, and a time stamp for the problem event isgenerated by a wireless network serving the mobile device. A position ofthe mobile device is marked by a network event symbol of a circle with acrossing line embedded in a square at reference number 306. At 308, asecond periodic location of the mobile device is generated at thelocation event symbol next to reference number 308.

Utilizing the location information generated at reference numbers 302and 308, a first approximation of a route of travel of the mobile devicecan be generated. This first approximation is depicted by thedouble-ended arrow between reference numbers 302 and 308. Aninterpolated position 310 of the mobile device can be estimated alongthe first approximation of the route of travel at the time of networkevent 306. Interpolated position 310 can be generated from an averagespeed along the first approximation of the route of travel, and adifference in time of occurrence of network event 306 and periodiclocations 302 and 308.

At 312, a second call initiation/termination 312 occurs at a known time.A position of the mobile device is marked by the call symbol next toreference number 312. A second approximation of the route of travel ofthe mobile device is depicted by the longer double-ended arrow extendingfrom reference number 302 to a third periodic position location 314.Additionally, a revised interpolated position 316 of the mobile devicecan be generated at the time of the network event along the secondapproximation of the route of travel. In this instance, the revisedinterpolated position 316 is closer to the actual location of the mobiledevice at a time of problem event 306, thereby improving the positionestimate. In other cases, however, a revised interpolated position 316may not be closer to the actual position of the mobile device at problemevent 306. In such cases, having knowledge of topographical informationof geographic region 300, including routes of travel and modes of travelof the geographic region 300, can potentially improve the estimatesignificantly (e.g., see FIG. 4, infra).

At 318, a second problem event occurs at a location identified by thenetwork event symbol next to reference number 318. An extrapolatedposition estimate 320 for the mobile device can be generated at the timeof network event 318. The extrapolated position can be generated byextending the first approximation of the route of travel or the secondapproximation of the route of travel beyond reference number 314. A timeof network event 318 can be utilized at least in conjunction with a timeof third periodic position location 314 (and potentially utilizing timeand positions—where available—of call 312, second periodic positionlocation 308, interpolated position 310, revised interpolated position316, call 304, or first periodic position location 302) to generate aspeed estimate of the mobile device along the extended approximation ofthe route of travel. The speed estimate can be utilized to locate themobile device along the extended route of travel at the time of networkevent 318 to arrive at extrapolated position 320.

FIG. 4 illustrates a diagram of an example topographical map 400 for ageographic region, which can be utilized for estimating mobile positionlocations according to still other aspects of the subject disclosure.Wireless communication services can be provided to the geographic regionby a radio access network of a mobile network (not depicted). Severalnetwork events as well as a travel route of a mobile device withintopographical map 400 are depicted. A legend correlates graphicalsymbols with respective types of network events. An X embedded in asquare is a location event symbol that represents a position of themobile device at a periodic location determination for the mobiledevice, a check mark embedded in a square is a call symbol thatindicates a position of the mobile device at a call initiation ortermination event, and a circle with a diagonal line embedded in asquare is a problem event symbol that indicates a position of the mobiledevice at the time of a problem event associated with the mobile device.In addition, the gold line represents a travel route of the mobiledevice throughout topographical map 400.

Topographical map 400 can be selected based at least in part on a speedof the mobile device, as described herein. Particularly, where the speedof the mobile device corresponds with a rate of travel that best fits aparticular mode of travel, a topographical map representing theparticular mode of travel can be selected, as described herein. Thus,topographical map 400 illustrating a network of city roads could beemployed in response to determining a motorized vehicle mode of travelbest fits the speed of the mobile device.

Several network events associated with the mobile device are depicted ontopographical map 400. The network events are numbered in chronologicalorder according to time of occurrence. The chronological order beginswith the mobile device in the lower right corner of topographical map400, with a call initiated at call symbol 402, followed shortlythereafter with a periodic position location determination 404 for themobile device. A second periodic position location determination 406occurs at the point indicated, and a call drop occurs for the mobiledevice at a problem event 408. Thereafter, a call is initiated at callsymbol 410, and a third periodic position location determination 412occurs shortly thereafter.

Utilizing location and time information at least of periodic positionlocation determination events 404, 406 and 412, a best fit route oftravel can be identified for the mobile device by determining a mode oftravel and identifying within topographical map 400 suitable routes forthe mode of travel. As an example, if a motorized vehicle mode of travelis determined, suitable routes can be limited to roads, highways, etc.,within topographical map 400. By limiting the mobile device to suitableroutes, a large portion of topographical map 400 can be eliminated,significantly increasing accuracy of position estimates of the mobiledevice. For instance, as compared with simple extrapolation orinterpolation techniques utilized for geographic region 300 of FIG. 3, amuch more accurate estimation of mobile device position can be made ascompared with linear extrapolation or interpolation between two or morepoints.

Upon identifying a best fit route of travel for mobile device, anestimate of mobile device position at a time of problem event 408 can bemade that is confined to the best fit route of travel. A position alongthe best fit route of travel at a time of problem event 408 can bedetermined by extrapolating a ratio of the time of problem event 408 andduration between position location determinations 406 and 412, to aratio of estimated position and length along the best fit route oftravel between locations of position location determinations 406 and412, and solving for the estimated position.

In at least one aspect of the subject disclosure, the position estimatecan be refined according to traffic information pertaining to trafficspeeds on the best fit route of travel, or respective traffic speeds onsegments of the best fit route of travel, where available. For instance,where traffic information indicates traffic speed on North Ave NE(coinciding with position location determination 406) is 25 miles perhour, speed on W Peachtree St NW is 35 miles per hour, and speed onPonce de Leon Ave NE is 40 miles per hour, the position estimate can berefined based on suitable relationships of these speeds and calculateddurations for which the mobile device is estimated to be on theserespective roads. Accordingly, employing topographical map 400 andsuitable routes of travel therein can significantly improve positionlocation estimates of the mobile device, where precise locationinformation is not known (e.g., in between periodic positiondeterminations). Moreover, the position location estimates can berefined along a best fit route of travel based on traffic speedinformation for the best fit route of travel.

FIG. 5 illustrates a block diagram of an example system 500 that can beconfigured to acquire network information for estimating mobile positionlocations associated with network events, according to further aspectsof the subject disclosure. System 500 can comprise an event locationsystem 502 configured to generate the position locations of the mobiledevice at points in time coinciding with network events associated withthe mobile device. A communication interface 504 can be employed fortransmitting and receiving data over a network interface with networkcomponents. Data received can be provided to an estimation engine 506configured to employ time and location data acquired by communicationinterface 504 for estimating the position of the mobile device at thetimes coinciding with network events.

As depicted, a real-time location server 508 can be configured toacquire and store mobile device location data and associated respectivetimes thereof. The mobile device location data can comprisenetwork-generated data, or mobile-device generated data. Moreover, thelocation data can be periodic, non-periodic, random or pseudo-random, orsubscriber originated. At least a subset of mobile device location dataalso includes respective time stamp data pertaining to a particularlocation determination for the mobile device.

Additionally, a network event server 510 can acquire informationpertaining to network events, including time of the network event,mobile device(s) affected by the network events, cell sites associatedwith the network events, or the like, or a suitable combination thereof.Upon occurrence of a network event, network event server 510 cantransmit acquired information pertaining to the network event to eventlocation system 502. Event location system 502 can determine a time ofthe network event from the acquired information and an identifier for amobile device affected by or reporting the network event. Event locationsystem 502 can then receive position location information for the mobiledevice from real-time location server 508 at times near the time of thenetwork event. The position location information can be requested byevent location system 502, or can be automatically sent by real-timelocation server 508 in response to a notification of the network eventoriginating from network event server 510.

Event location system can also query or otherwise obtain traffic speeddata from a traffic server 512. The traffic speed data can be employedin conjunction with determining a speed of the mobile device for one ormore times, or refining a speed estimate. In some aspects, traffic speeddata can be utilized in conjunction with fitting position location datato a route of travel for the mobile device near a time of the networkevent. In other aspects, traffic speed data can be utilized to refine aposition of the mobile device along a route of travel that has beenselected for the mobile device.

Upon arriving at a position estimate or refined position estimate forthe mobile device at a time of the network event, event location system502 can output the refined position estimate to a network event modelingentity 514. The position estimate can be sent alone, or in conjunctionwith the network event data received from network event server 510. Theposition estimate can be utilized by network event modeling entity toimprove estimates of a location of the network event itself. Whenutilized for multiple network events over time, network event modelingin general can be greatly improved. Particularly, event modeling can beperformed with greater spatial resolution, providing more accurateinformation about the location of network events, thereby improvingcapability of network technicians of discovering a source of such eventsand potentially reducing the cost of such discovery. Accordingly, system500 can provide significant benefits for wireless network operators inmaintaining and optimizing wireless networks.

The aforementioned systems have been described with respect tointeraction between several systems, components or communicationinterfaces. It should be appreciated that such systems and componentscan include those components or sub-components specified therein, someof the specified components or sub-components, or additional components.For example, a system could include event location system 102 comprisingmobile estimation engine 200, real-time location server 508, networkevent server 510 and traffic server 512, or a different combination ofthese or other entities. Sub-components could also be implemented asmodules communicatively coupled to other modules rather than includedwithin parent modules. Additionally, it should be noted that one or morecomponents could be combined into a single component providing aggregatefunctionality. For instance, calculation component 112 can includetopography selection component 124, or vice versa, to facilitateestimating mobile device position and selecting topographical data inconjunction with the estimating, by way of a single component. Thecomponents can also interact with one or more other components notspecifically described herein but known by those of skill in the art.

FIGS. 6, 7 and 8 illustrate various methods in accordance with one ormore of the various embodiments disclosed herein. While, for purposes ofsimplicity of explanation, the methods are shown and described as aseries of acts, it is to be understood and appreciated that the variousembodiments are not limited by the order of acts, as some acts may occurin different orders or concurrently with other acts from that shown anddescribed herein. For example, those skilled in the art will understandand appreciate that a method could alternatively be represented as aseries of interrelated states or events, such as in a state diagram.Moreover, not all illustrated acts may be required to implement a methodin accordance with the various embodiments. Additionally, it should befurther appreciated that the methods disclosed hereinafter andthroughout this specification are capable of being stored on an articleof manufacture to facilitate transporting and transferring such methodsto computers. The term article of manufacture, as used herein, isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media.

FIG. 6 illustrates a flowchart of an example method 600 of operating asystem that includes at least one processor to provide improved mobiledevice positioning according to aspects of the subject disclosure. At602, method 600 can comprise receiving, by the system, a first datainput indicative of a first geographic location of a mobile device. Themethod can also comprise receiving, by the system, informationindicative of a first time at which the geographic location of themobile device is determined. At 604, method 600 can comprise receiving,by the system, a second data input indicative of a second geographiclocation of the mobile device. Moreover, the second data input caninclude information indicative of a second time at which the secondgeographic location of the mobile device is determined. At 606, method600 can comprise receiving, by the system, indication of a network eventpertaining to the mobile device. The indication of the network event caninclude information indicative of a third time at which the networkevent occurs. At 608, method 600 can comprise deriving, by the system, aposition of the mobile device at the third point in time based at leaston the first data input and the second data input, and associating thederived position of the mobile device with the network event. Method 600can also comprise outputting, by the system, the derived position to acomponent of a wireless network related to storing network eventinformation. Such a component can also be configured for compiling timeand location information of network events.

FIG. 7 illustrates a flowchart of an example method 700 according tostill other aspects of the subject disclosure. At 702, method 700 cancomprise receiving a first mobile data location indicative of a firstgeographic location of a mobile device, and a first time stampcorresponding with the first mobile data location. At 704, method 700can comprise receiving a second mobile data location indicative of asecond geographic location of the mobile device, and a second time stampcorresponding with the second mobile data location. At 706, method 700can comprise receiving data indicative of a network event pertaining tothe mobile device. At 708, method 700 can comprise receiving callorigination/termination data near a time of the network event. The callorigination/termination data can include respective time stamps forrespective call origination events or call termination events pertainingto the mobile device. Additionally, the call origination/terminationdata can include respective location determinations for a subset of thecall origination events or call termination events.

At 710, method 700 can comprise estimating a speed of the mobile devicenear the time of the network event. Speed can be estimated utilizingtime and location information of the mobile device acquired from thefirst mobile data location, second mobile data location, as well as oneor more other mobile data locations, and call origination/terminationdata near the time of the network event, or a subset thereof. In atleast one aspect, the estimated speed can be refined utilizing trafficspeeds within a vicinity of the mobile device near the time of thenetwork event. The traffic speeds can be particular to a mode of travelidentified for the mobile device. For instance, upon acquiring aninitial speed estimate, a route of travel can be identified and trafficinformation for that route of travel obtained. Utilizing the trafficinformation, accuracy of the identified mode of travel and route oftravel can be re-analyzed and re-configured at least in part from thetraffic speed data for the route of travel. Where speed estimates of themobile device do not match the traffic speed data, re-analysis cancomprise updating speed estimates, analyzing other potential modes oftravel or routes of travel, or the like, to improve a best fit for themode of travel or the route of travel, or a suitable combinationthereof. In other words, the traffic speeds can be utilized as afeedback input to verify or constrain initial data inputs for estimatedspeed calculations, mode of travel selections, or route of travelselections.

At 712, method 700 can comprise referencing topographical informationnearing a pre-defined vicinity of the first geographic location, thesecond geographic location or the network event. At 714, method 700 cancomprise determining a mode of travel for the mobile device. Suitablemodes of travel can comprise motorized modes of travel, cycling modes oftravel, or pedestrian modes of travel, or the like. The mode of travelcan be determined at least in part from comparing an estimate of speedof the mobile device to predetermined ranges of speed associated withrespective modes of travel.

At 716, method 700 can comprise accessing topography information fromthe topography map pertinent to the determined mode of travel. At 718,method 700 can comprise accessing contemporary speeds of travelpertinent to the mode of travel. The speeds of travel can be concurrentspeeds (e.g., real-time) or post-processed information at a previoustime coinciding with the time of the network event. At 720, method 700can comprise identifying a route of travel of the mobile device from thetime and location information of the mobile device, the estimated speedinformation, or a combination thereof. At 722, method 700 can comprisereferencing the route of travel with the mobile location and timeinformation to position the mobile device along the route of travelaccording to the time information.

Referring now to FIG. 8, method 700 continues at 724 and performs adetermination as to whether a suitable match exists between geographiclocation of route of travel and the mobile location and timeinformation. If so, method 700 proceeds to 726. Otherwise, method 700proceeds to 728.

At 726, method 700 can comprise determining mobile device position alongthe route of travel on the topographical map at the time of the networkevent 726. The position can be refined by interpolating or extrapolatingmobile device time and location information with traffic speed data forthe route of travel or respective traffic speeds for respective subsetsof the route of travel. From 726, method 700 can proceed to 730.

At 728, method 700 can comprise extrapolating or interpolating aposition of the mobile device directly from time and location data, inresponse to failing to identify a route of travel for the mobile device.The position of the mobile device can be refined utilized generaltraffic speeds for the vicinity of the network event to attempt toimprove the position. From 728, method 700 can proceed to 730.

At 730, method 700 can comprise outputting an estimated position of themobile device in response to receiving the data indicative of thenetwork event. At 732, method 700 can comprise updating network eventmodeling with the estimated position. At 734, method 700 can compriseacquiring user or device submitted mobile location data near a time ofthe network event. The user or device submitted mobile location data canbe acquired, for instance, from a third-party network server thatprovides user-submitted locations services, and makes acquired dataavailable for network modeling functionality. At 736, method 700 cancomprise refining the estimated position with the user or devicesubmitted data. For instance, where user or device submitted data isavailable at a later time than network-generated information, the useror device submitted data (e.g., GPS data, . . . ) can be used to furtherrefine estimated mobile device positions, as well as test accuracy ofmobile position estimations utilizing techniques disclosed herein. At738, method 700 can comprise uploading refined position estimates forrefining, updating or appending network event modeling.

FIG. 9 illustrates an example apparatus 900 for implementing networkevent modeling for wireless networking according to further aspects ofthe subject disclosure. For instance, apparatus 900 can reside at leastpartially within a wireless communication network and/or within awireless receiver such as a node, base station, access point, userterminal, personal computer coupled with a mobile interface card, or thelike. It is to be appreciated that apparatus 900 is represented asincluding functional blocks, which can be functional blocks thatrepresent functions implemented by a hardware, software, or combinationthereof (e.g., firmware). In some aspects, the functional blocks canrepresent non-transitory computer-readable media. In other aspects, thefunctional blocks can represent transitory computer-readable media.

Apparatus 900 can comprise a computer-readable medium 902 comprising oneor more computer-executable instructions that can be accessed over adata communication interface 904. Data communication interface 904 caninclude a communication bus, a media reader (e.g., disc reader, diskreader, drive reader, . . . ), a data ribbon, a wired data interface, awireless data interface, a network communication interface, a networksignaling interface, or a suitable combination thereof. Additionally,the computer-executable instructions can be stored in an operatingmemory 908 or executed by a processor 906 to facilitate functionality ofapparatus 900.

As depicted, computer-readable medium 902 can comprise a firstcomputer-executable instruction 910 for acquiring mobile position andcorresponding time data and network event data. Particularly, theposition data can be for times near a time of occurrence of a networkevent. Additionally, computer-readable medium 902 can comprise a secondcomputer-executable instruction 912 for acquiring topography andconcurrent travel rate data for a geographic location related to theposition data. Computer-readable medium 902 can also comprise a thirdcomputer-executable instruction 914 can be configured for employing aset of known geographic locations for the mobile device at respectivepredetermined times for extrapolating or interpolating an additionalposition of the mobile device at a time coinciding with the networkevent involving the mobile device. In some aspects, the extrapolating orinterpolating can employ the topographical data related to the positiondata. In a particular aspect, the extrapolating or interpolating canemploy a route of travel pertaining to the topographical data. In atleast one alternative or additional aspect, the extrapolating orinterpolating can employ the concurrent travel rate data pertinent tothe route of travel. In addition to the foregoing, computer-readablemedium 902 can comprise a fourth executable instruction 916 that can beconfigured for outputting the extrapolated additional position of themobile device as an estimated position of the network event. This outputcan be employed for improving accuracy of network event modeling.

Referring now to FIG. 10, illustrated is a schematic block diagram of anillustrative mobile device 1000 capable of maintaining concurrentwireless communication with a radio access network and an access pointbase station, in accordance with some embodiments described herein.Although a mobile handset 1000 is illustrated herein, it will beunderstood that other devices can be a mobile device, and that themobile handset 1000 is merely illustrated to provide context for theembodiments described herein. The following discussion is intended toprovide a brief, general description of an example of a suitableenvironment 1000 in which some of the various disclosed embodiments canbe facilitated or implemented. While the description includes a generalcontext of computer-executable instructions embodied on a computerreadable storage medium, those skilled in the art will recognize thatthe various aspects also can be implemented in combination with otherprogram modules or as a combination of hardware, software or firmware.

Applications (e.g., program modules) can include routines, programs,components, data structures, etc., that perform particular tasks orimplement particular abstract data types. Moreover, those skilled in theart will appreciate that the methods described herein can be practicedwith other system configurations, including single-processor ormultiprocessor systems, minicomputers, mainframe computers, as well aspersonal computers, hand-held computing devices, microprocessor-based orprogrammable consumer electronics, and the like, each of which can beoperatively coupled to one or more associated devices. Further,illustrated aspects of the subject disclosure can be practiced indistributed computing environments where certain tasks are performed byremote processing devices that are linked through a communicationsnetwork (e.g., mobile handset 1000 communicating through a mobilecommunication network). In a distributed computing environment, systemsand system components, as well as program modules can be located in bothlocal and remote memory storage devices.

A computing device such as mobile handset 1000 can include a variety ofmedia, which can include computer-readable storage media orcommunication media, which two terms are used herein differently fromone another as follows.

Computer readable storage media can be any available storage media thatcan be accessed by a computer (e.g., mobile handset 1000) and includesboth volatile and nonvolatile media, removable and non-removable media.By way of example and not limitation, computer-readable storage mediacan be implemented in connection with any method or technology forstorage of information, such as computer-readable instructions, datastructures, program modules or unstructured data. Computer-readablestorage media can include, but is not limited to, RAM, ROM, EEPROM,flash memory or other memory technology, CD ROM, digital versatile disk(DVD) or other optical disk storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or othertangible or non-transitory media which can be used to store desiredinformation. Computer-readable storage media can be accessed by one ormore local or remote computing devices, e.g., via access requests,queries or other data retrieval protocols, for a variety of operationswith respect to the information stored by the medium.

Communication media embodies computer-readable instructions, datastructures, program modules or other structured or unstructured data ina modulated data signal such as a carrier wave or other transportmechanism, and includes any suitable information delivery or transportmedia. The term “modulated data signal” or signals means a signal thathas one or more of its characteristics set or changed in such a manneras to encode information in one or more signals. By way of example, andnot limitation, communication media includes wired media such as a wirednetwork or direct-wired connection, and wireless media such as acoustic,RF, infrared and other wireless media.

Mobile handset 1000 includes a processor 1002 for controlling andprocessing onboard operations and functions. A memory 1004 interfaces tothe processor 1002 for storage of data and one or more applications 1006(e.g., user-generated service feedback, network event feedback,user-originated mobile location transmission, etc.). Other applicationscan include voice recognition of predetermined voice commands thatfacilitate receipt of user input. The applications 1006 can be stored inthe memory 1004 and/or in a firmware 1008, and executed by the processor1002 from either or both the memory 1004 or the firmware 1008. Thefirmware 1008 can also store startup code for execution in initializingmobile handset 1000. A communications component 1010 interfaces to theprocessor 1002 to facilitate wired/wireless communication with externalsystems, e.g., cellular networks, VoIP networks, Wi-Fi networks, and soon. Here, the communications component 1010 can also include a suitablecellular transceiver 1011A (e.g., a global system for mobilecommunication (GSM) transceiver, a code division multiple access (CDMA)transceiver, . . . ) or an unlicensed transceiver 1011B (e.g., Wi-Fi,WiMAX) for corresponding signal communications. Mobile handset 1000 canbe a device such as a cellular telephone, a PDA with mobilecommunications capabilities, and messaging-centric devices, and so on.The communications component 1010 can also facilitate communicationsreception from terrestrial radio networks (e.g., broadcast), digitalsatellite radio networks, and Internet-based radio services networks.

Mobile handset 1000 includes a display 1012 for displaying text, images,video, telephony functions (e.g., a Caller ID function), setupfunctions, and for user input. For example, the display 1012 can also bereferred to as a “screen” that can accommodate the presentation ofmultimedia content (e.g., music metadata, messages, wallpaper, graphics,video, etc.). The display 1012 can also display videos and canfacilitate the generation, editing and sharing of graphical or videoapplications. A serial I/O interface 1014 is provided in communicationwith the processor 1002 to facilitate wired and/or wireless serialcommunications (e.g., USB, and/or IEEE 1094) through a hardwireconnection, and other serial input devices (e.g., a keyboard, keypad,and mouse). This supports updating and troubleshooting mobile handset1000, for example. Audio capabilities are provided with an audio I/Ocomponent 1016, which can include a speaker for the output of audiosignals related to, for example, indication that the user pressed theproper key or key combination to initiate the user feedback signal. Theaudio I/O component 1016 also facilitates the input of audio signalsthrough a microphone to record data and/or telephony voice data, and forinputting voice signals for telephone conversations.

Mobile handset 1000 can include a slot interface 1018 for accommodatinga SIC (Subscriber Identity Component) in the form factor of a cardSubscriber Identity Module (SIM) or universal SIM 1020, and interfacingthe SIM card 1020 with the processor 1002. However, it is to beappreciated that the SIM card 1020 can be manufactured into the handset1000, and updated by downloading data and software.

The handset 1000 can process IP data traffic through the communicationcomponent 1010 to accommodate IP traffic from an IP network such as, forexample, the Internet, a corporate intranet, a home network, a personalarea network, etc., through an ISP or broadband cable provider. Thus,VoIP traffic can be utilized by the handset 1000 and IP-based multimediacontent can be received in either an encoded or decoded format.

A graphics processing component 1022 (e.g., a camera) can be providedfor decoding encoded multimedia content. The graphics processingcomponent 1022 can aid in facilitating the generation, playback, editingand sharing of graphical media. Mobile handset 1000 also includes apower source 1024 in the form of batteries and/or an AC power subsystem,which power source 1024 can interface to an external power system orcharging equipment (not shown) by a power I/O component 1026.

Mobile handset 1000 can also include a video component 1030 forprocessing video content received and, for recording and transmittingvideo content. For example, the video component 1030 can facilitate thegeneration, editing and sharing of video media. A location trackingcomponent 1032 facilitates geographically locating mobile handset 1000.A user input component 1034 facilitates the user inputting information,responses or selections into mobile handset 1000. The user inputcomponent 1034 can include such input device technologies such as akeypad, keyboard, mouse, stylus pen, or touch screen, for example.

Referring again to the applications 1006, a location component 1036facilitates user-originated transmission of position location data formobile handset 100 to a network serving mobile handset 1000. A feedbackcomponent 1038 can be provided that facilitates user-originated problemevent reporting, for instance when a call drops or when service isdeemed to be poor by the subscriber. The applications 1006 can alsoinclude a client 1042 that provides at least the capability ofdiscovery, play and store of multimedia content, for example, music.

Mobile handset 1000, as indicated above relates to the communicationscomponent 1010, includes an indoor network radio transceiver 1011B(e.g., Wi-Fi transceiver). This function supports the indoor radio link,such as IEEE 802.11 (a, b, g, n, . . . ), and other 802.xx protocols(e.g., BlueTooth, Zigbee, . . . ) in the event mobile handset 1000comprises a dual-mode handset. Mobile handset 1000 can accommodate atleast satellite radio services through a handset that can combinewireless voice and digital radio chipsets into a single handheld device.

FIG. 11 illustrates a block diagram of an example embodiment of anaccess point (AP 1105) to implement and exploit one or more features oraspects of the disclosed subject matter. For instance, AP 1105 canfacilitate network-generated position determinations for mobile device,whether periodic, non-periodic, and so on. Moreover, AP 1105 can includeone or more network-based systems or components disclosed herein,including event location system 102 of FIG. 1, estimation engine 200 ofFIG. 2, event location system 502 of FIG. 5, etc.

In embodiment 1100, AP 1105 can receive and transmit signal(s) (e.g.,attachment signaling) from and to wireless devices like accessterminals, wireless ports and routers, wireless handsets, Femto cellterminals, or the like, through a set of antennas 1120 ₁-1020 _(N) (N isa positive integer). It should be appreciated that antennas 1120 ₁-1020_(N) can comprise electronic components and associated circuitry thatprovides for processing and manipulation of received signal(s) andsignal(s) to be transmitted. In an aspect, communication platform 1115includes a receiver/transmitter 1116 that can convert wireless signalsfrom analog to digital upon reception, and from digital to analog upontransmission. In addition, receiver/transmitter 1116 can divide a singledata stream into multiple, parallel data streams, or perform areciprocal operation. Coupled to receiver/transmitter 1116 is amultiplexer/demultiplexer 1117 that facilitates manipulation of signalin time and frequency space. Electronic component 1117 can multiplexinformation (data/traffic and control/signaling) according to variousmultiplexing schemes such as time division multiplexing (TDM), frequencydivision multiplexing (FDM), orthogonal frequency division multiplexing(OFDM), code division multiplexing (CDM), space division multiplexing(SDM), . . . . In addition, multiplexer/demultiplexer component 1117 canscramble and spread information (e.g., codes) according to substantiallyany code known in the art; e.g., Hadamard-Walsh codes, Baker codes,Kasami codes, polyphase codes, and so on. A modulator/demodulator 1118is also a part of communication platform 1115, and can modulateinformation according to multiple modulation techniques, such asfrequency modulation, amplitude modulation (e.g., M-ary quadratureamplitude modulation (QAM), with M a positive integer), phase-shiftkeying (PSK), and the like. Communication platform 1115 can also includea coder/decoder (codec) component 1119 that facilitates decodingreceived signal(s), and coding signal(s) to convey.

Access point 1105 also includes a processor 1135 configured to conferfunctionality, at least in part, to substantially any electroniccomponent in AP 1105. In particular, processor 1135 can facilitatedetermination of propagation delay information of RF signal, ormicrowave signal, among communication platform 1115 and antennas 1120₁-1020 _(N), whether alone or in conjunction with one or more otherAP(s) (not depicted), to facilitate generation of network-originatedposition information of a mobile device in accordance with variousaspects and embodiments disclosed herein. Power supply 1125 can attachto a power grid and include one or more transformers to achieve powerlevel that can operate AP 1105 components and circuitry. Additionally,power supply 1125 can include a rechargeable power component to ensureoperation when AP 1105 is disconnected from the power grid, or ininstances, the power grid is not operating.

Processor 1135 can also be functionally connected to communicationplatform 1115 and can facilitate operations on data (e.g., symbols,bits, or chips) for multiplexing/demultiplexing, such as effectingdirect and inverse fast Fourier transforms, selection of modulationrates, selection of data packet formats, inter-packet times, etc.Moreover, processor 1135 can be functionally connected, via a data orsystem bus, to calibration platform 1112 and other components (notshown) to confer, at least in part functionality to each of suchcomponents.

In AP 1105, memory 1145 can store data structures, code instructions andprogram modules, system or device information, code sequences forscrambling, spreading and pilot transmission, location intelligencestorage, determined delay offset(s), over-the-air propagation models,and so on. Processor 1135 is coupled to the memory 1145 in order tostore and retrieve information necessary to operate and/or conferfunctionality to communication platform 1115, calibration platform 1112,and other components (not shown) of access point 1105.

FIG. 12 presents an example embodiment 1200 of a mobile network platform1210 that can implement and exploit one or more aspects of the disclosedsubject matter described herein. For instance, mobile network platform1210 can be utilized by, or at least in part subsumed within, network402 of FIG. 4. In another aspect, mobile network(s) 104 or 502 caninclude, in whole or in part, mobile network platform 1210. In yet otheraspects, mobile network platform 1210 can control or provide networkfunctionality for Wi-Fi AP 204, 608A, 608B or 608C, or for macro basestation 206, 304, 604A, 604B or 604C, or a suitable combination thereof.

Mobile network platform 1210 can include components, e.g., nodes,gateways, interfaces, servers, or disparate platforms, that facilitateboth packet-switched (PS) (e.g., internet protocol (IP), frame relay,asynchronous transfer mode (ATM)) and circuit-switched (CS) traffic(e.g., voice and data), as well as control generation for networkedwireless telecommunication. Mobile network platform 1210 includes CSgateway node(s) 1212 which can interface CS traffic received from legacynetworks like telephony network(s) 1240 (e.g., public switched telephonenetwork (PSTN), or public land mobile network (PLMN)) or a signalingsystem #7 (SS7) network 1260. Circuit switched gateway node(s) 1212 canauthorize and authenticate traffic (e.g., voice) arising from suchnetworks. Additionally, CS gateway node(s) 1212 can access mobility, orroaming, data generated through SS7 network 1260; for instance, mobilitydata stored in a visited location register (VLR), which can reside inmemory 1230. Moreover, CS gateway node(s) 1212 interfaces CS-basedtraffic and signaling and PS gateway node(s) 1218. As an example, in a3GPP UMTS network, CS gateway node(s) 1212 can be realized at least inpart in gateway GPRS support node(s) (GGSN). It should be appreciatedthat functionality and specific operation of CS gateway node(s) 1212, PSgateway node(s) 1218, and serving node(s) 1216, is provided and dictatedby radio technology(ies) utilized by mobile network platform 1210 fortelecommunication.

In the disclosed subject matter, in addition to receiving and processingCS-switched traffic and signaling, PS gateway node(s) 1218 can authorizeand authenticate PS-based data sessions with served mobile devices. Datasessions can include traffic, or content(s), exchanged with networksexternal to the mobile network platform 1210, like wide area network(s)(WANs) 1250, enterprise network(s) 1270, and service network(s) 1280,which can be embodied in local area network(s) (LANs), can also beinterfaced with mobile network platform 1210 through PS gateway node(s)1218. It is to be noted that WANs 1250 and enterprise network(s) 1260can embody, at least in part, a service network(s) like IP multimediasubsystem (IMS). Based on radio technology layer(s) available intechnology resource(s) 1217, packet-switched gateway node(s) 1218 cangenerate packet data protocol contexts when a data session isestablished; other data structures that facilitate routing of packetizeddata also can be generated. To that end, in an aspect, PS gatewaynode(s) 1218 can include a tunnel interface (e.g., tunnel terminationgateway (TTG) in 3GPP UMTS network(s) (not shown)) which can facilitatepacketized communication with disparate wireless network(s), such asWi-Fi networks. In at least one aspect, the networks external to themobile network platform can comprise a network for generating, storing,acquiring or outputting traffic speed information for one or moregeographic regions, which can include traffic server 512 of FIG. 5,supra.

In embodiment 1200, mobile network platform 1210 also includes servingnode(s) 1216 that, based upon available radio technology layer(s) withintechnology resource(s) 1217, convey the various packetized flows of datastreams received through PS gateway node(s) 1218. It is to be noted thatfor technology resource(s) 1217 that rely primarily on CS communication,server node(s) can deliver traffic without reliance on PS gatewaynode(s) 1218; for example, server node(s) can embody at least in part amobile switching center. As an example, in a 3GPP UMTS network, servingnode(s) 1216 can be embodied in serving GPRS support node(s) (SGSN).

For radio technologies that exploit packetized communication, server(s)1214 in mobile network platform 1210 can execute numerous applications(e.g., location services, wireless device management, identifying nearbyWi-Fi access points, estimating position data for suitable mobiledevices outside periodic location determinations, . . . ) that cangenerate multiple disparate packetized data streams or flows, and manage(e.g., schedule, queue, format, duplicate, direct, . . . ) such flows.Such application(s) can include add-on features to standard services(for example, provisioning, billing, customer support . . . ) providedby mobile network platform 1210. Data streams (e.g., content(s) that arepart of a voice call or data session) can be conveyed to PS gatewaynode(s) 1218 for authorization/authentication and initiation of a datasession, and to serving node(s) 1216 for communication thereafter. Inaddition to the application server, server(s) 1214 can include operatorsystems for acquiring network event or mobile position locationinformation, such as real-time location server 508 or network eventserver 510 of FIG. 5, supra. Moreover, server(s) 1214 can includeutility server(s), a utility server can include a provisioning server,an operations and maintenance server, a security server that canimplement at least in part a certificate authority and firewalls as wellas other security mechanisms, and the like. In an aspect, securityserver(s) secure communication served through mobile network platform1210 to ensure network's operation and data integrity in addition toauthorization and authentication procedures that CS gateway node(s) 1212and PS gateway node(s) 1218 can enact. Moreover, provisioning server(s)can provision services from external network(s) like networks operatedby a disparate service provider; for instance, WAN 1250 or GlobalPositioning System (GPS) network(s) (not shown). Provisioning server(s)can also provision coverage through networks associated to mobilenetwork platform 1210 (e.g., deployed and operated by the same serviceprovider), such as Femto cell network(s) or Wi-Fi network(s) (not shown)that enhance wireless service coverage within indoor or confined spacesand offload or share RAN resources in order to enhance subscriberservice experience within a home or business environment.

It is to be noted that server(s) 1214 can include one or more processorsconfigured to confer at least in part the functionality of macro networkplatform 1210. To that end, the one or more processors can execute codeinstructions stored in memory 1230, for example.

In example embodiment 1200, memory 1230 can store information related tooperation of mobile network platform 1210. In particular, memory 1230can include contents of topography database 210 in example estimationengine 200. Other operational information can include provisioninginformation of mobile devices served through wireless platform network1210, subscriber databases; application intelligence, pricing schemes,e.g., promotional rates, flat-rate programs, subscription services whichcan include an IP session persistence service; technicalspecification(s) consistent with telecommunication protocols foroperation of disparate radio, or wireless, technology layers; and soforth. Memory 1230 can also store information from at least one oftelephony network(s) 1240, WAN 1250, SS7 network 1260, enterprisenetwork(s) 1270 or service network(s) 1280.

It is to be noted that aspects, and features of the disclosed subjectmatter described in the subject specification can be exploited insubstantially any wireless communication technology. For instance,Wi-Fi, WiMAX, Enhanced GPRS, 3GPP LTE, 3GPP2 UMB, 3GPP UMTS, HSPA,HSDPA, HSUPA, GERAN, UTRAN, LTE Advanced. Additionally, substantiallyall aspects of the disclosed subject matter as disclosed in the subjectspecification can be exploited in legacy telecommunication technologies;e.g., GSM. In addition, mobile as well non-mobile networks (e.g.,internet, data service network such as internet protocol television(IPTV)) can exploit aspects or features described herein.

Various aspects or features described herein can be implemented as amethod, apparatus or system, or article of manufacture using standardprogramming or engineering techniques. In addition, various aspects orfeatures disclosed in the subject specification also can be effectedthrough program modules that implement at least one or more of themethods disclosed herein, the program modules being stored in a memoryand executed by at least a processor. Other combinations of hardware andsoftware or hardware and firmware can enable or implement aspectsdescribed herein, including disclosed method(s). The term “article ofmanufacture” as used herein is intended to encompass a computer programaccessible from any computer-readable device, carrier, or media. Forexample, computer readable media can include but are not limited tomagnetic storage devices (e.g., hard disk, floppy disk, magnetic strips. . . ), optical discs (e.g., compact disc (CD), digital versatile disc(DVD), blu-ray disc (BD) . . . ), smart cards, and flash memory devices(e.g., card, stick, key drive . . . ).

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Processors can exploit nano-scale architectures suchas, but not limited to, molecular and quantum-dot based transistors,switches and gates, in order to optimize space usage or enhanceperformance of user equipment. A processor may also be implemented as acombination of computing processing units.

In the subject specification, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory.

By way of illustration, and not limitation, nonvolatile memory caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable ROM (EEPROM), or flashmemory. Volatile memory can include random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), anddirect Rambus RAM (DRRAM). Additionally, the disclosed memory componentsof systems or methods herein are intended to comprise, without beinglimited to comprising, these and any other suitable types of memory.

What has been described above includes examples of systems and methodsthat provide aspects of the disclosed subject matter. It is, of course,not possible to describe every conceivable combination of components ormethodologies for purposes of describing the disclosed subject matter,but one of ordinary skill in the art may recognize that many furthercombinations and permutations of the subject matter are possible.Furthermore, to the extent that the terms “includes,” “has,”“possesses,” and the like are used in the detailed description, claims,appendices and drawings such terms are intended to be inclusive in amanner similar to the term “comprising” as “comprising” is interpretedwhen employed as a transitional word in a claim.

What is claimed is:
 1. A method, comprising: receiving, by a systemcomprising a processor, a first data input indicative of a firstgeographic location of a mobile device at a first instance of time;receiving, by the system, a second data input indicative of a secondgeographic location of the mobile device at a second instance of time;estimating, by the system, a speed of the mobile device based at leastin part on the first geographic location, the first instance of time,the second geographic location and the second instance of time;receiving, by the system, event information at a third instance of time,wherein the event information represents a mobile communication networkevent affecting communication between the mobile communication networkand the mobile device; interpolating, by the system, a location of themobile device at the third instance of time based at least on the speedof the mobile device, the first data input and the second data input;and associating, by the system, the location of the mobile device at thethird instance of time with the mobile communication network event. 2.The method of claim 1, further comprising receiving, by the system, athird data input indicative of a third geographic location of the mobiledevice at a fourth instance of time, wherein the fourth instance of timeis later than the first instance of time and the second instance oftime.
 3. The method of claim 2, further comprising estimating, by thesystem, a revised speed of the mobile device based at least in part onthe third geographic location, the fourth instance of time and at leastone of: the second geographic location and the second instance of time;or the first geographic location and the first instance of time.
 4. Themethod of claim 3, further comprising determining, by the system, arevised location of the mobile device at the third instance of timebased at least on the revised speed of the mobile device, the third datainput and at least one of: the first data input or the second datainput.
 5. The method of claim 4, further comprising associating, by thesystem, the revised location of the mobile device at the third instanceof time with the mobile communication network event.
 6. The method ofclaim 2, further comprising receiving, by the system, second eventinformation at a fifth instance of time, wherein the second eventinformation represents a second mobile communication network eventaffecting the communication between the mobile communication network andthe mobile device.
 7. The method of claim 6, further comprisingextrapolating, by the system, a second location of the mobile device atthe fifth instance of time, based at least on the speed of the mobiledevice, the third data input and one or more of: the first data input orthe second data input.
 8. The method of claim 1, further comprising:employing, by the system, road network information in conjunction withthe location of the mobile device or the speed of the mobile device todetermine a road of a road network that coincides with the location ofthe mobile device at the third instance of time; revising, by thesystem, the location of the mobile device utilizing geographicboundaries of the road of the road network; and generating, by thesystem, revised location data for the mobile device indicative of arevised location of the mobile device at the third instance of time. 9.The method of claim 8, further comprising: obtaining, by the system,vehicle speed information for the road of the road network at the thirdinstance of time; revising, by the system, the speed of the mobiledevice based at least in part on the vehicle speed information; andgenerating, by the system, revised speed data indicative of a revisedspeed of the mobile device at the third instance of time.
 10. The methodof claim 9, further comprising: further revising, by the system, therevised location of the mobile device at the third instance of timeutilizing the revised speed data; generating, by the system, secondrevised location data for the mobile device indicative of a secondrevised location of the mobile device at the third instance of time; andassociating, by the system, the mobile communication network event withthe second revised location of the mobile device at the third instanceof time.
 11. A system, comprising: a processor; and a memory that storesexecutable instructions that, when executed by the processor, facilitateperformance of operations, comprising: receiving location datacomprising respective location information pertaining to a mobile devicefor distinct points in time; determining a speed of the mobile devicefrom the respective location information and the distinct points intime; receiving a notification of a network event pertaining to themobile device and a time of the network event; estimating a position ofthe mobile device at the time of the network event utilizing therespective location information and the speed of the mobile device, thedistinct points in time, and the time of the network event; andgenerating output information that associates the position of the mobiledevice with a geographic location of the network event.
 12. The systemof claim 11, wherein the operations further comprise determining whetherthe mobile device is moving at a motor vehicle rate based on the speedof the mobile device.
 13. The system of claim 12, wherein the operationsfurther comprise refining the position of the mobile device or the speedof the mobile device utilizing road data of a road network and speeddata of vehicles on the road network at the time of the network event.14. The system of claim 11, wherein the operations further comprisedetermining whether the mobile device is moving at a cycling rate basedon the speed of the mobile device.
 15. The system of claim 14, whereinthe operations further comprise refining the position of the mobiledevice at the time of the network event utilizing cycling route data ofa cycling route map.
 16. The system of claim 11, wherein the operationsfurther comprise determining whether the mobile device is moving at apedestrian rate based on the speed of the mobile device.
 17. The systemof claim 16, wherein the operations further comprise refining theposition of the mobile device at the time of the network event utilizingpedestrian route data of a pedestrian map.
 18. The system of claim 11,wherein the operations further comprise: acquiring navigationaldevice-submitted location information pertaining to the network eventfrom a navigational device system serving a navigational deviceassociated with the mobile device; and refining the position of themobile device during the time of the network event as a function of thenavigational device-submitted location information.
 19. A method,comprising: employing, by a system comprising a processor, a group ofknown geographic locations for a mobile device and associated respectivetimes, and a speed of the mobile device to determine another location ofthe mobile device at a time of occurrence of a network event associatedwith the mobile device, wherein the group of known geographic locationsfor the mobile device exclude the other location determined from thegroup of known geographic locations and the associated respective timesof the mobile device; and outputting, by the system, the other locationof the mobile device determined from the group of known geographiclocations and the associated respective times as an estimated positionof the network event for the time of occurrence.
 20. The method of claim19, further comprising: determining, by the system, a mode of travel forthe mobile device at least in part from the speed of the mobile device;identifying, by the system, routes of travel within a pre-determinedvicinity of the group of known geographic locations that satisfy a firstdefined function with respect to the mode of travel; fitting, by thesystem, the group of known geographic locations to the routes of traveland determining a best fit route of travel for the mobile device fromthe routes of travel; and revising, by the system, the other location ofthe mobile device utilizing geographic data representing a geographicboundary of the best fit route of travel, resulting in an updated otherlocation.